LLM RELIABILITY STANDARD

The reliability standard
for production AI.

Every model measured for reliability before you ship, every answer checked in production after — the hallucinations that survive both never reach your users.

14LLMs evaluated
4Reliability metrics
liveResults stream in
$0Free to start

// SEE IT IN ACTION

One question. Every model. Scored live.

Watch a sample evaluation stream in on the left — then run the very same flow on your own data on the right. No fake numbers: the live tool scores against the ground truth you provide.

SAMPLE EVALUATIONlive

Q: What is our refund window?

Claude Sonnetscoring…
GPT-5.5scoring…
Gemini 3.5 Proscoring…
Sonar Proscoring…
Grok 4.3scoring…

sample data · scored deterministically against ground truth

// WHY IT MATTERS

An LLM hallucination is a confident, fluent answer that is simply wrong.

When you ship an LLM feature, you are trusting the model to be right every time — and it will not be. A single fabricated policy, price, or fact erodes user trust the instant it reaches someone. The hard part is not generating an answer; it is knowing which answers you can trust.

HallucinationLab measures how often each model hallucinates on your data, deterministically — never an LLM grading another LLM — so you can choose, monitor, and guard the right model with evidence instead of guesswork. Read the methodology →

// HOW IT WORKS

From evaluation to production reliability.

01 —

Evaluate on your domain

Bring your own questions and ground truth. We fan out to every major LLM and score across four reliability metrics in real time.

02 —

Deploy with confidence

The hlabs SDK sits between your app and the LLM. Every response is checked before your users see it — bad answers never reach them.

03 —

Optimize continuously

Reports surface the real cost of every hallucination, so you know exactly when to switch models before your users notice.

// THE PLATFORM

Three tools, one reliability loop.

EVALUATE

Benchmark every model on your data

Paste a question and the correct answer, pick your models, and watch faithfulness, accuracy, relevance, and hallucination rate stream in side by side. Bring your own keys — your data and keys never touch our servers.

Open the evaluator →
faithfulness0.96
hallucinated1 / 14
latency1.2s

hlabs SDK

Catch hallucinations in production

One import sits between your app and any LLM. Every response is scored in real time; when an answer does not hold up, the SDK automatically retries or falls back to a more reliable model — before your user ever sees it.

Explore the SDK →
caughtlive
retryauto
fallbackauto

DASHBOARD

Track reliability over time

Every evaluation you run is saved to your account, so you can compare models across weeks, watch regressions, and prove which model to trust with a record instead of a hunch.

View the dashboard →
historysaved
trendweekly
exportsoon

// THE FOUR RELIABILITY METRICS

What “reliable” actually measures.

Faithfulness

Is the answer grounded in the provided source material, with no invented facts?

Accuracy

Does the answer match the known ground-truth answer for the question?

Relevance

Does the answer actually address what was asked, without drifting off-topic?

Hallucination rate

How often does the model fabricate information that is not supported at all?

// WHERE IT MATTERS MOST

Built for the answers you cannot get wrong.

💬

Customer support

Refund windows, policies, entitlements — a confidently wrong reply costs a ticket and a customer.

⚕️

Healthcare

Dosages, eligibility, guidance. Fabricated medical facts are not an option; every answer must be grounded.

💳

Finance

Rates, fees, compliance language. Hallucinated numbers create real liability and regulatory risk.

⚖️

Legal

Citations, clauses, precedent. The infamous fake-case problem is exactly what deterministic scoring catches.

// TRUST BY DESIGN

A reliability tool has to be trustworthy itself.

Your keys never leave your browser

API keys live only in your session and call the providers directly from your machine. We never store or log them.

Deterministic, not vibes

Scores come from fixed logic against your ground truth — never a second LLM's opinion. A grader that can hallucinate cannot certify reliability.

Your data stays yours

Prompts and answers are processed for your evaluation only. Nothing is used to train anything.

Still have questions?

How detection works, key privacy, supported models, and more.

Read the FAQ →

EARLY ACCESS · hlabs SDK BETA

Get the SDK before everyone else.

The evaluation tool is free and open today. The waitlist is for what is next: the hlabs SDK — a drop-in layer that catches hallucinations in your production app before your users ever see them. It scores every response for faithfulness in real time, then automatically retries or falls back to a more reliable model when an answer does not hold up.

  • ✓ Priority beta invites, rolled out in waves
  • ✓ Free for the whole beta — no credit card
  • ✓ A direct line to the team to shape the API
  • ✓ Early reliability reports for your own models

One email when your invite is ready. No spam, unsubscribe anytime.